Education, Science, Technology, Innovation and Life
Open Access
Sign In

A Circle Detection Algorithm Based on Ellipse Removal

Download as PDF

DOI: 10.23977/jipta.2021.41007 | Downloads: 47 | Views: 1808


Shuyi Guo 1, Sai Yang 1, Pengbo Zhang 1


1 School of Mechanical Engineering, North China University of Water Resources and Electric Power, Zhengzhou Henan 450045, China

Corresponding Author

Shuyi Guo


In optical CCD detection, due to distortion, the circle will appear elliptical shape after projection onto a two-dimensional plane through perspective. In order to solve this problem, a circle detection algorithm based on ellipse de-falsification was proposed. The image was preprocessed by filtering, the axial ratio of the distorted circle was set, and the ten points randomly selected on the contour of the image were used to determine whether the circle was within the reasonable distortion range. Quadratic interpolation method was used to detect the sub-pixel edge of the contour point set, and based on the principle of Random Sampling Consensus (RANSAC), the outliers outside the threshold range were removed to achieve the effect of false elimination. Finally, the distorted circle was fitted by the least square method. Experimental results show that the detection error of this method is about 0.3%.


Perspective projection; Ellipse removal; Subpixel edge; Outlier; Distortion circle


Shuyi Guo, Sai Yang, Pengbo Zhang. A Circle Detection Algorithm Based on Ellipse Removal. Journal of Image Processing Theory and Applications (2021) Vol. 4: 42-50. DOI:


[1] GUO J, YANG J. An iterative procedure for robust circle fitting. Communication in Statistics-Simulation and Computation, 2018, 47(11):1-8.9
[2] Ren Yongqiang, TU Dejiang, Han Shu. Measurement of Cylinder Liner Size of Diesel Engine Based on Machine Vision. Modular Machine Tool & Automatic Manufacturing Technology, 2020(09):151-153.
[3] Li Xiaobin, Cui Qingliang, Guo Yuming, Feng Junhui, Sun Jingxin, Zhang Yanqing. Research on subpixel measurement method of buckwheat grain triaxial size based on centroid method. Chinese journal of agricultural mechanization, 2017, 38(10):50-56.
[4]Xu L, OJA E.A new curve detection method: Randomized Hough transform (RHT).Pattern Recog.Lett., 1990, 11 (5) :331-338.
[5]Zhu Zhengwei, Song Wenhao, Jiao Zhuqing, et al. Fast circle detection algorithm based on improved randomized Hough transform. Computer Engineering and Design, 2018, 39 (7): 1978-1983.
[6] Jia Ming, Wu Liyong, Wang Linlin. A random circle detection algorithm based on gradient direction and probability estimation. Semiconductor optoelectronics, 2019, 40(01):102-107.
[7]Huang Y H, Chung K L, Yang W N, et al. Efficient symmetry-based screening strategy to speed up randomized circle-detection. Pattern Recog.Lett., 2012, 33 (16) :2071-2076.
[8] Hou Jiancheng, Liu Guohai, He Jianqiang, Wang Zhicheng. Improved center detection of random Hough transform. China test, 2020, 46(01):124-128.
[9]Chen T C, Chung K L. An efficient randomized algorithm for detecting circles. Computer Vision & Image Understanding, 2001, 83 (2):172-191.
[10] Yu Xiongchao, Hu Yongxiang, Yao Zhenqiang. Research on spot Distortion analysis and Correction Method of Laser Shot Peening 3d Scanning optical Path System for large Workpiece. China Mechanical Engineering Society special Processing Branch, Guangdong University of Technology. Intelligent and Precise Processing technology -- Proceedings of the 17th National Special Processing Academic Conference (Abstract). Special Processing Branch of China Mechanical Engineering Society, Guangdong University of Technology: China Mechanical Engineering Society, 2017:1.
[11] Yi Haolang. Research on Fast Ellipse Detection Algorithm Based on Multiple Delimitation. Donghua University, 2020.
[12]HEIKKLILA J, SILVEN O.A Four-step camera calibration procedure with implicit image correction. Washington: IEEE Computer Society Conference, 1997.
[13] Zhang Hu, DA Feipeng, Xing Dekui. Applied Optics, 2008(06):905-911. (in Chinese)
[14]OTSU N.A threshold selection method from gray level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9:62-66.
[15]Zhou, Xianen; Wang, Yaonan; Zhu, Qing; (2019). A surface defect detection framework for glass bottle bottom using visual attention model and wavelet transform. IEEE Transactions on Industrial Informatics, 1-1.

Downloads: 1353
Visits: 104233

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.